I am interested in structure and dynamics of complex networks. My research focuses on developing methods and algorithms for network abstraction, modeling, sampling and comparison, node clustering and partitioning, and node position and link analysis.
I am also interested in machine learning with graphs in general, and in graph representation learning and relational deep learning in particular.
My other fields of interest include selected areas of data analysis, data mining, stream mining and statistics.
For complete list of publications see my CV.
I teach BSc, MSc, and PhD courses in network science and analysis, machine learning with graphs, Python and Java programming, and databases and information systems. Some of my lectures are available on YouTube.
Many of the networks I have compiled are available through Netzschleuder, ICON and the Network Repository. For code see repositories netpy-workshop, node-intermediacy, graph-convexity, convex-skeleton, nets-nodegroups, etc.

Feel free to contact me, especially if you are interested in network science or machine learning with graphs.